31 Commits

Author SHA1 Message Date
snyk-bot
36b0a80384 fix: src/requirements.txt to reduce vulnerabilities
The following vulnerabilities are fixed by pinning transitive dependencies:
- https://snyk.io/vuln/SNYK-PYTHON-SETUPTOOLS-3113904
2022-11-15 12:03:37 +00:00
Dev Singh
de4d3d4967 Update README.md 2021-10-21 14:21:20 -05:00
Arthur Lu
d56411253c fixed badge url 2021-08-26 18:20:11 -07:00
Arthur Lu
c415225afe Update release badge 2021-08-26 18:11:25 -07:00
Arthur Lu
d684813ee0 Merge pull request #10 from titanscouting/automate-build
Automate build
2021-06-09 14:58:21 -07:00
Arthur Lu
26079f3180 fixed pathing for build-CLI.*
added temp directory to gitignore
2021-04-27 07:26:14 +00:00
Arthur Lu
99e722c400 removed ThreadPoolExecutor import 2021-04-25 06:05:33 +00:00
Arthur Lu
f5a0e0fe8c added sample build-cli workflow 2021-04-25 03:51:01 +00:00
Arthur Lu
28e423942f added .gitattributes 2021-04-15 19:41:10 +00:00
Arthur Lu
8977f8c277 added compiled binaries with no file endings
to gitignore
2021-04-13 04:05:46 +00:00
Arthur Lu
2b0f718aa5 removed compiled binaries
added compiled binaries in /dist/ to gitignore
2021-04-13 04:03:07 +00:00
Arthur Lu
30469a3211 removed matplotlib import
removed plotting pit analysis
fixed warning supression for win exe
superscript v 0.8.6
2021-04-12 15:13:54 -07:00
Arthur Lu
391d4e1996 created batch script for windows compilation 2021-04-12 14:39:00 -07:00
Arthur Lu
224f64e8b7 better fix for devcontainer.json 2021-04-12 06:30:21 +00:00
Arthur Lu
aa7d7ca927 quick patch for devcontainer.json 2021-04-12 06:27:50 +00:00
Arthur Lu
d10c16d483 superscript v 0.8.5 2021-04-10 06:08:18 +00:00
Arthur Lu
f211d00f2d superscript v 0.8.4 2021-04-09 23:45:16 +00:00
Arthur Lu
69c707689b superscript v 0.8.3 2021-04-03 20:47:45 +00:00
Arthur Lu
d2f9c802b3 built and verified threading fixes 2021-04-02 22:04:06 +00:00
Arthur Lu
99e28f5e83 fixed .gitignore
added build-CLI script
fixed threading in superscript
2021-04-02 21:58:35 +00:00
Arthur Lu
18dbc174bd deleted config.json
changed superscript config lookup to relative path
added additional requirements to requirements.txt
added build spec file for superscript
2021-04-02 21:35:05 +00:00
Arthur Lu
79689d69c8 fixed spelling in default config,
added config to git ignore
2021-04-02 01:28:25 +00:00
Dev Singh
80c3f1224b Merge pull request #3 from titanscouting/superscript-main
Merge initial changes
2021-04-01 13:40:29 -05:00
Dev Singh
960a1b3165 fix ut and file structure 2021-04-01 13:38:53 -05:00
Arthur Lu
89fcd366d3 Merge branch 'master' into superscript-main 2021-04-01 11:34:44 -07:00
Dev Singh
79cde44108 Create SECURITY.md 2021-04-01 13:11:38 -05:00
Dev Singh
2b896db9a9 Create MAINTAINERS 2021-04-01 13:11:22 -05:00
Dev Singh
483897c011 Merge pull request #1 from titanscouting/add-license-1
Create LICENSE
2021-04-01 13:11:03 -05:00
Dev Singh
9287d98fe2 Create LICENSE 2021-04-01 13:10:50 -05:00
Dev Singh
991751a340 Create CONTRIBUTING.md 2021-04-01 13:10:14 -05:00
Dev Singh
9d2476b5eb Create README.md 2021-04-01 13:09:18 -05:00
16 changed files with 325 additions and 243 deletions

View File

@@ -1,2 +1,7 @@
FROM python
WORKDIR ~/
FROM ubuntu:20.04
WORKDIR /
RUN apt-get -y update
RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends tzdata
RUN apt-get install -y python3 python3-dev git python3-pip python3-kivy python-is-python3 libgl1-mesa-dev build-essential
RUN ln -s $(which pip3) /usr/bin/pip
RUN pip install pymongo pandas numpy scipy scikit-learn matplotlib pylint kivy

View File

@@ -0,0 +1,2 @@
FROM titanscout2022/tra-analysis-base:latest
WORKDIR /

View File

@@ -1,7 +1,7 @@
{
"name": "TRA Analysis Development Environment",
"build": {
"dockerfile": "Dockerfile",
"dockerfile": "dev-dockerfile",
},
"settings": {
"terminal.integrated.shell.linux": "/bin/bash",
@@ -24,5 +24,5 @@
"ms-python.python",
"waderyan.gitblame"
],
"postCreateCommand": "apt install vim -y ; pip install -r src/requirements.txt ; pip install pylint ; pip install tra-analysis; pip install pytest"
}
"postCreateCommand": "/usr/bin/pip3 install -r ${containerWorkspaceFolder}/src/requirements.txt && /usr/bin/pip3 install --no-cache-dir pylint && /usr/bin/pip3 install pytest"
}

4
.gitattributes vendored Normal file
View File

@@ -0,0 +1,4 @@
# Auto detect text files and perform LF normalization
* text=auto eol=lf
*.{cmd,[cC][mM][dD]} text eol=crlf
*.{bat,[bB][aA][tT]} text eol=crlf

17
.github/workflows/build-cli.yml vendored Normal file
View File

@@ -0,0 +1,17 @@
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
name: Superscript Unit Tests
on:
release:
types: [published, edited]
jobs:
generate:
name: Build Linux
runs-on: ubuntu-latest
steps:
- name: Checkout master
uses: actions/checkout@master

View File

@@ -17,8 +17,6 @@ jobs:
matrix:
python-version: [3.7, 3.8]
env:
working-directory: ./data-analysis/
steps:
- uses: actions/checkout@v2
@@ -30,9 +28,7 @@ jobs:
run: |
python -m pip install --upgrade pip
pip install pytest
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
working-directory: ${{ env.working-directory }}
if [ -f src/requirements.txt ]; then pip install -r src/requirements.txt; fi
- name: Test with pytest
run: |
pytest
working-directory: ${{ env.working-directory }}
pytest test/

9
.gitignore vendored
View File

@@ -4,6 +4,11 @@
**/.pytest_cache/
**/*.pyc
**/build/
**/*.egg-info/
**/dist/
**/config.json
**/tra_analysis/
**/temp/*
**/errorlog.txt
/dist/superscript.*
/dist/superscript

View File

@@ -1,6 +1,7 @@
BSD 3-Clause License
Copyright (c) 2020, Titan Scouting
Copyright (c) 2021, Titan Scouting
All rights reserved.
Redistribution and use in source and binary forms, with or without

View File

@@ -1,45 +1,46 @@
# Red Alliance Analysis · ![GitHub release (latest by date)](https://img.shields.io/github/v/release/titanscout2022/red-alliance-analysis)
Titan Robotics 2022 Strategy Team Repository for Data Analysis Tools. Included with these tools are the backend data analysis engine formatted as a python package, associated binaries for the analysis package, and premade scripts that can be pulled directly from this repository and will integrate with other Red Alliance applications to quickly deploy FRC scouting tools.
---
# `data-analysis`
To facilitate data analysis of collected scouting data in a user firendly tool, we created the data-analysis application. At its core it uses the tra-analysis package to conduct any number of user selected tests on data collected from the TRA scouting app. It uploads these tests back to MongoDB where it can be viewed from the app at any time.
The data-analysis application also uses the TRA API to interface with MongoDB and uses the TBA API to collect additional data (match win/loss).
The application can be configured with a configuration tool or by editing the config.json directly.
## Prerequisites
---
Before installing and using data-analysis, make sure that you have installed the folowing prerequisites:
- A common operating system like **Windows** or (*most*) distributions of **Linux**. BSD may work but has not been tested nor is it reccomended.
- [Python](https://www.python.org/) version **3.6** or higher
- [Pip](https://pip.pypa.io/en/stable/) (installation instructions [here](https://pip.pypa.io/en/stable/installing/))
## Installing Requirements
---
Once navigated to the data-analysis folder run `pip install -r requirements.txt` to install all of the required python libraries.
## Scripts
---
The data-analysis application is a collection of various scripts and one config file. For users, only the main application `superscript.py` and the config file `config.json` are important.
To run the data-analysis application, navigate to the data-analysis folder once all requirements have been installed and run `python superscript.py`. If you encounter the error:
`pymongo.errors.ConfigurationError: Empty host (or extra comma in host list).`
don't worry, you may have just not configured the application correctly, but would otherwise work. Refer to [the documentation](https://titanscouting.github.io/analysis/data_analysis/Config) to learn how to configure data-analysis.
---
# Build Statuses
![Superscript Unit Tests](https://github.com/titanscout2022/red-alliance-analysis/workflows/Superscript%20Unit%20Tests/badge.svg?branch=master)
# Red Alliance Analysis · ![GitHub release (latest by date)](https://img.shields.io/github/v/release/titanscouting/tra-superscript)
Titan Robotics 2022 Strategy Team Repository for Data Analysis Tools. Included with these tools are the backend data analysis engine formatted as a python package, associated binaries for the analysis package, and premade scripts that can be pulled directly from this repository and will integrate with other Red Alliance applications to quickly deploy FRC scouting tools.
---
# `data-analysis`
To facilitate data analysis of collected scouting data in a user firendly tool, we created the data-analysis application. At its core it uses the tra-analysis package to conduct any number of user selected tests on data collected from the TRA scouting app. It uploads these tests back to MongoDB where it can be viewed from the app at any time.
The data-analysis application also uses the TRA API to interface with MongoDB and uses the TBA API to collect additional data (match win/loss).
The application can be configured with a configuration tool or by editing the config.json directly.
## Prerequisites
---
Before installing and using data-analysis, make sure that you have installed the folowing prerequisites:
- A common operating system like **Windows** or (*most*) distributions of **Linux**. BSD may work but has not been tested nor is it reccomended.
- [Python](https://www.python.org/) version **3.6** or higher
- [Pip](https://pip.pypa.io/en/stable/) (installation instructions [here](https://pip.pypa.io/en/stable/installing/))
## Installing Requirements
---
Once navigated to the data-analysis folder run `pip install -r requirements.txt` to install all of the required python libraries.
## Scripts
---
The data-analysis application is a collection of various scripts and one config file. For users, only the main application `superscript.py` and the config file `config.json` are important.
To run the data-analysis application, navigate to the data-analysis folder once all requirements have been installed and run `python superscript.py`. If you encounter the error:
`pymongo.errors.ConfigurationError: Empty host (or extra comma in host list).`
don't worry, you may have just not configured the application correctly, but would otherwise work. Refer to [the documentation](https://titanscouting.github.io/analysis/data_analysis/Config) to learn how to configure data-analysis.
---
# Build Statuses
Coming soon!

5
build/build-CLI.bat Normal file
View File

@@ -0,0 +1,5 @@
set pathtospec="../src/superscript.spec"
set pathtodist="../dist/"
set pathtowork="temp/"
pyinstaller --onefile --clean --distpath %pathtodist% --workpath %pathtowork% %pathtospec%

5
build/build-CLI.sh Normal file
View File

@@ -0,0 +1,5 @@
pathtospec="../src/superscript.spec"
pathtodist="../dist/"
pathtowork="temp/"
pyinstaller --onefile --clean --distpath ${pathtodist} --workpath ${pathtowork} ${pathtospec}

View File

@@ -1,101 +0,0 @@
{
"max-threads": 0.5,
"team": "",
"competition": "",
"key": {
"database": "",
"tba": ""
},
"statistics": {
"match": {
"balls-blocked": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-collected": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-lower-teleop": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-lower-auto": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-started": [
"basic_stats",
"historical_analyss",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-upper-teleop": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
],
"balls-upper-auto": [
"basic_stats",
"historical_analysis",
"regression_linear",
"regression_logarithmic",
"regression_exponential",
"regression_polynomial",
"regression_sigmoidal"
]
},
"metric": {
"elo": {
"score": 1500,
"N": 400,
"K": 24
},
"gl2": {
"score": 1500,
"rd": 250,
"vol": 0.06
},
"ts": {
"mu": 25,
"sigma": 8.33
}
},
"pit": {
"wheel-mechanism": true,
"low-balls": true,
"high-balls": true,
"wheel-success": true,
"strategic-focus": true,
"climb-mechanism": true,
"attitude": true
}
}
}

View File

@@ -2,4 +2,18 @@ requests
pymongo
pandas
tra-analysis
kivy==2.0.0rc2
dnspython
pyinstaller
requests
pymongo
numpy
scipy
scikit-learn
six
pyparsing
pandas
kivy==2.0.0rc2
setuptools>=65.5.1 # not directly required, pinned by Snyk to avoid a vulnerability

View File

@@ -3,10 +3,21 @@
# Notes:
# setup:
__version__ = "0.8.2"
__version__ = "0.8.6"
# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
0.8.6:
- added proper main function
0.8.5:
- added more gradeful KeyboardInterrupt exiting
- redirected stderr to errorlog.txt
0.8.4:
- added better error message for missing config.json
- added automatic config.json creation
- added splash text with version and system info
0.8.3:
- updated matchloop with new regression format (requires tra_analysis 3.x)
0.8.2:
- readded while true to main function
- added more thread config options
@@ -130,80 +141,97 @@ import os
from os import system, name
from pathlib import Path
from multiprocessing import Pool
import matplotlib.pyplot as plt
from concurrent.futures import ThreadPoolExecutor
import platform
import sys
import time
import warnings
# global exec_threads
global exec_threads
def main():
# global exec_threads
global exec_threads
sys.stderr = open("errorlog.txt", "w")
warnings.filterwarnings("ignore")
# while (True):
splash()
current_time = time.time()
print("[OK] time: " + str(current_time))
while (True):
config = load_config("red-alliance-analysis\data-analysis\config.json")
competition = config["competition"]
match_tests = config["statistics"]["match"]
pit_tests = config["statistics"]["pit"]
metrics_tests = config["statistics"]["metric"]
print("[OK] configs loaded")
try:
print("[OK] starting threads")
cfg_max_threads = config["max-threads"]
sys_max_threads = os.cpu_count()
if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
alloc_processes = sys_max_threads + cfg_max_threads
elif cfg_max_threads > 0 and cfg_max_threads < 1:
alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
alloc_processes = cfg_max_threads
elif cfg_max_threads == 0:
alloc_processes = sys_max_threads
else:
print("[Err] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
exit()
# exec_threads = Pool(processes = alloc_processes)
# print("[OK] " + str(alloc_processes) + " threads started")
current_time = time.time()
print("[OK] time: " + str(current_time))
apikey = config["key"]["database"]
tbakey = config["key"]["tba"]
print("[OK] loaded keys")
config = load_config("config.json")
competition = config["competition"]
match_tests = config["statistics"]["match"]
pit_tests = config["statistics"]["pit"]
metrics_tests = config["statistics"]["metric"]
print("[OK] configs loaded")
previous_time = get_previous_time(apikey)
print("[OK] analysis backtimed to: " + str(previous_time))
print("[OK] starting threads")
cfg_max_threads = config["max-threads"]
sys_max_threads = os.cpu_count()
if cfg_max_threads > -sys_max_threads and cfg_max_threads < 0 :
alloc_processes = sys_max_threads + cfg_max_threads
elif cfg_max_threads > 0 and cfg_max_threads < 1:
alloc_processes = math.floor(cfg_max_threads * sys_max_threads)
elif cfg_max_threads > 1 and cfg_max_threads <= sys_max_threads:
alloc_processes = cfg_max_threads
elif cfg_max_threads == 0:
alloc_processes = sys_max_threads
else:
print("[ERROR] Invalid number of processes, must be between -" + str(sys_max_threads) + " and " + str(sys_max_threads))
exit()
exec_threads = Pool(processes = alloc_processes)
print("[OK] " + str(alloc_processes) + " threads started")
print("[OK] loading data")
start = time.time()
match_data = load_match(apikey, competition)
pit_data = load_pit(apikey, competition)
print("[OK] loaded data in " + str(time.time() - start) + " seconds")
apikey = config["key"]["database"]
tbakey = config["key"]["tba"]
print("[OK] loaded keys")
print("[OK] running match stats")
start = time.time()
matchloop(apikey, competition, match_data, match_tests)
print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
previous_time = get_previous_time(apikey)
print("[OK] analysis backtimed to: " + str(previous_time))
print("[OK] running team metrics")
start = time.time()
metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
print("[OK] loading data")
start = time.time()
match_data = load_match(apikey, competition)
pit_data = load_pit(apikey, competition)
print("[OK] loaded data in " + str(time.time() - start) + " seconds")
print("[OK] running pit analysis")
start = time.time()
pitloop(apikey, competition, pit_data, pit_tests)
print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
set_current_time(apikey, current_time)
print("[OK] finished all tests, looping")
print("[OK] running match stats")
start = time.time()
matchloop(apikey, competition, match_data, match_tests)
print("[OK] finished match stats in " + str(time.time() - start) + " seconds")
# clear()
print("[OK] running team metrics")
start = time.time()
metricloop(tbakey, apikey, competition, previous_time, metrics_tests)
print("[OK] finished team metrics in " + str(time.time() - start) + " seconds")
print("[OK] running pit analysis")
start = time.time()
pitloop(apikey, competition, pit_data, pit_tests)
print("[OK] finished pit analysis in " + str(time.time() - start) + " seconds")
set_current_time(apikey, current_time)
print("[OK] finished all tests, looping")
print_hrule()
except KeyboardInterrupt:
print("\n[OK] caught KeyboardInterrupt, killing processes")
exec_threads.terminate()
print("[OK] processes killed, exiting")
exit()
else:
pass
#clear()
def clear():
@@ -215,11 +243,39 @@ def clear():
else:
_ = system('clear')
def print_hrule():
print("#"+38*"-"+"#")
def print_box(s):
temp = "|"
temp += s
temp += (40-len(s)-2)*" "
temp += "|"
print(temp)
def splash():
print_hrule()
print_box(" superscript version: " + __version__)
print_box(" os: " + platform.system())
print_box(" python: " + platform.python_version())
print_hrule()
def load_config(file):
config_vector = {}
with open(file) as f:
config_vector = json.load(f)
try:
f = open(file)
except:
print("[ERROR] could not locate config.json, generating blank config.json and exiting")
f = open(file, "w")
f.write(sample_json)
exit()
config_vector = json.load(f)
return config_vector
@@ -284,6 +340,8 @@ def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][
global exec_threads
short_mapping = {"regression_linear": "lin", "regression_logarithmic": "log", "regression_exponential": "exp", "regression_polynomial": "ply", "regression_sigmoidal": "sig"}
class AutoVivification(dict):
def __getitem__(self, item):
try:
@@ -314,14 +372,20 @@ def matchloop(apikey, competition, data, tests): # expects 3D array with [Team][
variable_data.append((data[team][variable], test))
test_filtered.append(test)
result_filtered = map(simplestats, variable_data)
result_filtered = exec_threads.map(simplestats, variable_data)
i = 0
result_filtered = list(result_filtered)
for result in result_filtered:
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result
filtered = test_filtered[i]
try:
short = short_mapping[filtered]
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result[short]
except KeyError: # not in mapping
return_vector[team_filtered[i]][variable_filtered[i]][test_filtered[i]] = result
i += 1
push_match(apikey, competition, return_vector)
@@ -510,27 +574,54 @@ def get_team_metrics(apikey, tbakey, competition):
return {"elo-ranks": elo_ranked, "glicko2-ranks": gl2_ranked}
def graph_pit_histogram(apikey, competition, figsize=(80,15)):
sample_json = """{
"max-threads": 0.5,
"team": "",
"competition": "2020ilch",
"key":{
"database":"",
"tba":""
},
"statistics":{
"match":{
"balls-blocked":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-collected":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-lower-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-started":["basic_stats","historical_analyss","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-teleop":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"],
"balls-upper-auto":["basic_stats","historical_analysis","regression_linear","regression_logarithmic","regression_exponential","regression_polynomial","regression_sigmoidal"]
pit = d.get_pit_variable_formatted(apikey, competition)
},
"metric":{
"elo":{
"score":1500,
"N":400,
"K":24
},
"gl2":{
"score":1500,
"rd":250,
"vol":0.06
},
"ts":{
"mu":25,
"sigma":8.33
}
},
"pit":{
"wheel-mechanism":true,
"low-balls":true,
"high-balls":true,
"wheel-success":true,
"strategic-focus":true,
"climb-mechanism":true,
"attitude":true
}
}
}"""
fig, ax = plt.subplots(1, len(pit), sharey=True, figsize=figsize)
i = 0
for variable in pit:
ax[i].hist(pit[variable])
ax[i].invert_xaxis()
ax[i].set_xlabel('')
ax[i].set_ylabel('Frequency')
ax[i].set_title(variable)
plt.yticks(np.arange(len(pit[variable])))
i+=1
plt.show()
main()
if __name__ == "__main__":
if sys.platform.startswith('win'):
multiprocessing.freeze_support()
main()

37
src/superscript.spec Normal file
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# -*- mode: python ; coding: utf-8 -*-
block_cipher = None
a = Analysis(['superscript.py'],
pathex=['/workspaces/tra-data-analysis/src'],
binaries=[],
datas=[],
hiddenimports=[
"dnspython",
"sklearn.utils._weight_vector",
"requests",
],
hookspath=[],
runtime_hooks=[],
excludes=[],
win_no_prefer_redirects=False,
win_private_assemblies=False,
cipher=block_cipher,
noarchive=False)
pyz = PYZ(a.pure, a.zipped_data,
cipher=block_cipher)
exe = EXE(pyz,
a.scripts,
a.binaries,
a.zipfiles,
a.datas,
[('W ignore', None, 'OPTION')],
name='superscript',
debug=False,
bootloader_ignore_signals=False,
strip=False,
upx=True,
upx_exclude=[],
runtime_tmpdir=None,
console=True )